1. SAMS AND MICRO-DATA: NEW AREAS OF RESEARCH Paul Schreyer OECD IIOA Towards New Horizons of Innovation, Environment and Trade Kitakyushu July 2013

2. 1.Measuring well-being and living standards - policy demand 2.Distributional information and the national accounts – bridging the gap 3.SAM as a tool to structure and analyse data 4.From SAMs to living standards Overview

3. 1. Measuring well-being and living standards - policy demand

4. While GDP is a key measure to monitor macro- economic activity, productivity, demand for paid-jobs GDP is not a metric for people’s well-being and is often at variance with people’s personal experiences Measuring well-being implies confronting values: from “treasuring what you measure” to “measuring what you treasure” Increasing recognition that…

5. UNDP Human Development Reports OECD Fora since 2003 Stiglitz-Sen-Fitoussi Commission (2009) EU: GDP and Beyond And significant interest at national and local level OECD How’s Life? Many activities

6. Dimensions – OECD Framework

7. Measuring Well-being requires looking at: – Households and people – Outcomes, not inputs or outputs – Assessing inequalities alongside averages

8. Apply criteria to measuring material well-being and living standards: – Households and people  institutional sectors – Outcomes  HH income and its components – Inequalities  HH distributional information This is exactly what SAMs have been conceived for So where do SAM and micro-data come in?

9. Richard Stone 1960s; Pyatt, Thorbecke 1970s Keunig (1994) Eurostat Handbook 2003 Use for development planning (Pyatt and Round 1977), Concept: consistent integration of: – SUTs or IOT – institutional sector accounts – socio-economic break-down of households or labour – national accounts matrix with expanded information on households or labour A little reminder on SAMS

10. National Accounts Matrix

11. SAM

12. For purpose at hand, SAMs are useful to: Systematise link between: – Primary income types: Wages and salaries Mixed income Gross operating surplus Other net taxes on production – Disposable income inequality = HHs grouped by quintiles, deciles, etc. Where does disposable income for a particular HH originate?

13. But there is a major statistical issue: NA aggregates and HH survey data on (income) distribution are inconsistent

14. 2. Distributional information and the national accounts – bridging the gap

15. Distributional information: bottom-up <- household surveys Average and macro information: top-down <- national accounts Conceptual differences: – Scope – Units (individuals vs households) – Definition of income Imputations: OOH, FISIM Empirical differences: – Property income (e.g., interest received) – Mixed income (self-employed) Survey information and national accounts 15

16. OECD-Eurostat Expert Group – To examine differences NA – Surveys – To develop NA-compatible distributional data – Income, consumption and savings for 16 countries Results forthcoming (Fesseau et al 2013)

17. Do NA-Survey differences matter? Yes. Adjustment coefficient for income components (NA/Survey ratio)

18. Data needed by groups of HHs

19.  Savings* as a percentage of adjusted disposable income, by income quintile 19 Example of disparity indicator: savings

20. 3. Back to the SAMS: A tool to structure and analyse data

21. New multipliers SAM flows for HH by type of HH But also: multipliers – Given a certain value-added generated in industries, what are the direct and indirect effects on HHs disposable income? Compare with traditional I/O multipliers: – Given a certain final demand, what are the direct and indirect effects on industries production and value-added?

22. Example: Portugese SAM (Reich 2012) For OECD work on well-being, classification by income group would be preferable No redistributional effect? Missing: STIK

23. Typical SAM does not cater for Social Transfers in Kind (STIK) Introduce adjusted disposable income and actual individual consumption Otherwise, measure of living standards incomplete To be developed…

24. Relative position of the 20% richest households to the 20% poorest households

25. From SAMs to measurement of living standards

26. Large body of literature Recent empirical studies – Jorgenson and Slesnick (2013) – Fleurbaey and Gaulier (2009) – Jones and Klenow (2011) – Fleurbaey and Blanchard (2012) (But not typically based on SAMs or on adjusted disposable income) Aggregate measures of material well- being (welfare economics)

27. Basic Idea AveragesDistribution

28. Jorgenson and Slesnick (2013) Measuring Social Welfare in the US National Accounts

29. Requires consistent information on HHs Micro – NA consistency would improve results in the literature that do not address this issue Best: structured in SAM Construction of index of living standards/material well-being

30. Increasing interest in measurement and analysis of well-being and living standards Requires: – consistent data on HH accounts, from primary to disposable income – Break down by socio-economic characteristics SAM is excellent accounting framework Few SAMs exist but clear policy demand may change this Summing up

31. Needed: bridge NA and micro survey data Also needed: consistency between micro data on consumption, income, wealth Summing up (2)

32. OECD guidance on the measurement of: Commercial break for recent OECD methodological publications 32  Micro Statistics on Household Wealth www.oecd.org/statistics/guidelines-for-micro- statistics-on-household-wealth.htm www.oecd.org/statistics/guidelines-for-micro- statistics-on-household-wealth.htm  the Distribution of Household Income, Consumption and Wealth www.oecd.org/statistics/ICW-Framework.htm www.oecd.org/statistics/ICW-Framework.htm

33. Looking ahead: – Microdata for STIKs – Microdata for bringing in non-market production and consumption – From (adjusted) disposable to full income For analysis, use SAM multipliers and plug into literature on welfare measurement There’s much work to be done! Summing up (2)

34. Thank you! Paul.Schreyer@oecd.org